Measuring Risk of Portfolio: GARCH-Copula Model

Chaker Aloui and Samia Ben Messaoud ()
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Samia Ben Messaoud: International Finance Grouup-Tunisia, Postal: ; Department of Economics, , International Finance Grouup-Tunisia,, Faculty of Management and Economics Sciences of Tunis, E1 Manar university, E1 Manar, PB.P 248. C.P.2092, Tunis,, Tunisia

Journal of Economic Integration, 2015, vol. 30, 172-205

Abstract: In this paper, we use the copulas functions in financial application, namely to examine the assumption of asymmetric dependence and to calculate some measures of risk. The first step consists of deducing filtered residuals for each return series by an asymmetric Glosten-Jagannathan-Runkle Generalized Autoregressive conditional Hetero skedasticity (GJR-GARCH) model. For the second step, we use an estimation of a Generalized Pareto Distribution for the upper and lower tails to determine the empirical semiparametric marginal Cumulative Distribution Function. In our approach, we propose to use a portfolio consisting of increments from five countries. The GJR-GARCH copula is then applied to the data and used to reduce correlation between the simulated residuals of each series. The marginal distributions of filtered residuals are fitted with a semi-parametric Cumulative Distribution Function using the copulas’ functions and Generalized Pareto Distribution for tails. For each series, we compute Value-at-Risk and Conditional Value-at-Risk.

Keywords: GJR-GARCH; Copula Model; Portfolio Risk; Value at Risk; Conditional Value at Risk (search for similar items in EconPapers)
JEL-codes: E32 F15 F42 (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:ris:integr:0656

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